How do species emerge?
How do new species break away from their ancestors to forge distinct eco-evolutionary roles?
It is not individual traits that survive, reproduce and die, but whole individuals. Selection on one trait can generate a response to selection in others. This evolutionary constraint is imposed by heredity, physiology or natural selection and can limit adaptation by channeling evolution in the direction of least genetic resistance characterized by abundant phenotypic variability.
But if constraint only channels adaptation down predictable paths, how do new species break away from their ancestors to forge distinct eco-evolutionary roles? Despite Simpson’s 'choppy sea' metaphor of a dynamic adaptive landscape, the location and topology of fitness peaks are ubiquitously assumed constant.
The goal of this PhD is to track how morphological variance-covariance matrices differ during the emergence of new species, searching for 'tipping points' in the dynamics of speciation to fill the empirical evidence gap of how evolutionary constraints change during the emergence of new species.
This project brings together comparative analytical techniques developed on ERC funded research in Goswami’s group with data gathered on NERC funded research in Ezard’s research group.
Quantitative morphological traits like size and shape are fundamental for adaptive evolution and preferable to a genetic approach here because the nature of inheritance is complex: phenotypes act as multi-gene signals of the response to selection pressure.
The methodology involved in the project uses existing 3d micro-tomographic reconstructions of almost 2000 individual foraminifera (at the time of writing, the data set will continue to expand during the project) in a paired sampling design of sister-species and ancestor-descendent pairs.
The abundant fossil record of planktonic foraminifera facilitates this high-resolution sampling of up to 30 time points through multiple putative speciation events.
The analytical approach builds on 3d methods for large-scale comparative analysis developed in the Goswami lab over years, including automated extraction of surface morphometric descriptors from the Euler characteristic.
All methods seek to identify how covariance matrices, which aggregate individual traits into composite axes, differ through time. The methods seek to identify shifts in rotation of axes, changes in variation composition among axes and changing importance of certain traits onto certain axes.
These metrics indicate whether diversification is locked into narrow bands or unconstrained morphologically, provide ratios of within- vs among-species variability and track how differences among individuals become differences among species.
The INSPIRE DTP program provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners.
The student will be registered at the University of Southampton and hosted for extended periods within Ocean and Earth Science at the National Oceanography Centre Southampton and the Natural History Museum London.
Depending on the applicant’s background, specific training can be provided in foraminiferal taxonomy, data management, statistical computing, multivariate statistics and geometric morphometrics.
The project is suitable for applicants interested in fundamental questions in evolutionary biology; all statistical training can be provided during the project for the right candidate.
Eligibility and how to apply
Read how to apply on the INSPIRE website.
The deadline for applications is 4 January 2021.
Nosil, P., Feder, J., Flaxman, S., Gompert, Z. 2017 Tipping points in the dynamics of speciation. Nat Ecol Evol 1, 0001.
Goswami A, Smaers JB, Soligo C, Polly PD. 2014 The macroevolutionary consequences of phenotypic integration: from development to deep time. Phil. Trans. R. Soc. B 369: 20130254.
Zhang, W., Ezard, T., Searle-Barnes, A., Brombacher, A., Katsamenis, O. and Nixon, M. 2020 Towards Understanding Speciation By Automated Extraction And Description Of 3d Foraminifera Stacks, 2020 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIA) pp. 30-33.
This a joint PhD training partnership between the Natural History Museum and INSPIRE a NERC Doctoral Training Partnership (DTP) creating an innovative multi-disciplinary experience for the effective training of future leaders in environmental science, engineering, technology development, business, and policy.